Multi label Classification using Keras
For a simple multi layer perceptron, you can refer to here: 
https://www.kaggle.com/fchollet/simple-deep-mlp-with-keras

This is a great resource for kerad multi input label classification. Also, here is a few reminders for implementing such classification model.

One hot encoding

In the sample data you provided, it seems like you are using raw numbers as input. This will create unnecessary complications for the model. A better approach will be to encode them into a vector with 0 in all except one index with 1. The index will be the numerical value you are encoding. For example, 1 will be 01000000... Till end of your range of input, and 2 will be 001000 and so on. If you have decimal values, then this approach isn't for you. However you should still scale down your input to something smaller like 0-1. 

output encoding

The output seems to be text, which cannot be done and also complicates the problem. Instead you can also use one hot encoding for the output. For example, let A be 0, B be 1, C be 2... AA be 27.... Until your list ends. And then use one hot encoding to encode them to vector of 0 and 1. 

Hope I can help you.